AWS Lambda is a serverless computing platform that lets users run code without provisioning or managing servers. With Lambda, users can run code for virtually any type of app or backend service—all with zero administration. It takes of requirements to run and scale code with high availability.
The Salesforce Platform is designed for building and deploying scalable cloud applications with managed hardware provisioning and app stacks. Lightning Web Components are used by developers to build reusable UI components.
Lambda excels at event-driven, short-lived tasks, such as processing files or building simple APIs. However, it's less ideal for long-running, computationally intensive, or applications that rely on carrying the state between jobs. Cold starts and constant load can easily balloon the costs.
If you have a large customer base and a large amount of data on each of your customers, it is really strong in creating personalized content that your salespeople can use in their pitch meetings—and then setting up workflows for automated for lifecycle journey creations to automatically go out to customers.
Developing test cases for Lambda functions can be difficult. For functions that require some sort of input it can be tough to develop the proper payload and event for a test.
For the uninitiated, deploying functions with Infrastructure as Code tools can be a challenging undertaking.
Logging the output of a function feels disjointed from running the function in the console. A tighter integration with operational logging would be appreciated, perhaps being able to view function logs from the Lambda console instead of having to navigate over to CloudWatch.
Sometimes its difficult to determine the correct permissions needed for Lambda execution from other AWS services.
I give it a seven is usability because it's AWS. Their UI's are always clunkier than the competition and their documentation is rather cumbersome. There's SO MUCH to dig through and it's a gamble if you actually end up finding the corresponding info if it will actually help. Like I said before, going to google with a specific problem is likely a better route because AWS is quite ubiquitous and chances are you're not the first to encounter the problem. That being said, using SAM (Serverless application model) and it's SAM Local environment makes running local instances of your Lambdas in dev environments painless and quite fun. Using Nodejs + Lambda + SAM Local + VS Code debugger = AWESOME.
It's very good, but it's still living in a little bit in an older design aspect, but I think a lot of it is about to come out, just hasn't quite gotten there yet. Still a little clunky from a you have to know it to know it or you know it to use it. It takes a little bit of training to get into it. It's not quite the, anybody can come in and start using it immediately, type feel.
Amazon consistently provides comprehensive and easy-to-parse documentation of all AWS features and services. Most development team members find what they need with a quick internet search of the AWS documentation available online. If you need advanced support, though, you might need to engage an AWS engineer, and that could be an unexpected (or unwelcome) expense.
I am not an administrator so there may very well be outstanding Support and I am just not privy to it. On a user level it's hard to gauge the effectiveness and responsiveness of Support because nearly everything has to go through an administrator
AWS Lambda is good for short running functions, and ideally in response to events within AWS. Google App Engine is a more robust environment which can have complex code running for long periods of time, and across more than one instance of hardware. Google App Engine allows for both front-end and back-end infrastructure, while AWS Lambda is only for small back-end functions
We were previously using an older version prior to it becoming Salesforce Lightning Platform so we were well adverse on the advantages of using a CRM, to begin with. It made sense to convert to Salesforce Lightning Platform after we were given a free trial of the platform. Certain reps were chosen to experiment with it and from there a decision was made to move forward. We've been customers ever since.
Positive - Only paying for when code is run, unlike virtual machines where you pay always regardless of processing power usage.
Positive - Scalability and accommodating larger amounts of demand is much cheaper. Instead of scaling up virtual machines and increasing the prices you pay for that, you are just increasing the number of times your lambda function is run.
Negative - Debugging/troubleshooting, and developing for lambda functions take a bit more time to get used to, and migrating code from virtual machines and normal processes to Lambda functions can take a bit of time.
